scholarly journals T90. QUANTIFYING THE CORE DEFICIT IN CLASSICAL SCHIZOPHRENIA

2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S265-S266 ◽  
Author(s):  
Mohanbabu Rathnaiah ◽  
Elizabeth Liddle ◽  
Lauren Gascoyne ◽  
Jyothika Kumar ◽  
Mohammad Katshu ◽  
...  
Keyword(s):  
Latent Variables ◽  
Latent Variable ◽  
Rating Scales ◽  
Mental Activity ◽  
Digit Symbol Substitution Test ◽  
Role Function ◽  
The Core ◽  
Plausible Candidate ◽  
Core Deficit ◽  
Impaired Cognition

Abstract Background For more than 100 years, disorganization and impoverishment of mental activity have been recognised as fundamental symptoms of schizophrenia. These symptoms may reflect a core brain process underlying persisting disability. Predisposition to persisting disability is a clinically important aspect of schizophrenia, yet the psychopathological processes predisposing to persisting disability are poorly understood. The delineation of a putative core deficit associated with persisting disability would be of potentially great value in delineating the underlying pathological processes and eventually in enhancing treatment. Aims To derive scores for mental disorganization and impoverishment from commonly used rating scales, and test the hypothesis that disorganization and impoverishment, along with impaired cognition and role-function reflect a latent variable that is a plausible candidate for the putative core deficit. Methods In a group of 40 patients with schizophrenia, we tested the hypothesis that mental disorganization and impoverishment, along with impaired cognition and role-function reflect a latent variable that is a plausible candidate for the core deficit. We derived disorganization and impoverishment factors from three symptom scales: PANSS, SSPI and CASH. For each of the three scales, we demonstrated significant correlation between these factors and impaired role function assessed using the Social and Occupational Functioning Scale (SOFAS) and cognitive impairment measured using the Digit Symbol Substitution Test (DSST). We then assessed the relationship between this latent “core deficit” variable and Post Movement Beta Rebound (PMBR), measured using magnetoencephalography and associated with persisting brain disorders. Results A single factor model provided excellent fit for the four features of core deficit, requiring no further modifications. Results were consistently similar for measures from all three scales. χ2 value was non-significant (range: 0.30 to 2.13, df = 2, p > 0.35), GFI met the threshold of greater than 0.9 (range = .976 to .996) and RMSEA was lesser than 0.06 (range = 0.000 to 0.040). PMBR was found to be significantly reduced in the schizophrenia group compared to healthy controls (t (28) =44.2 ± 12.1, p = 0.001). PMBR was strongly correlated with disorganization (r (40) = .600, p=0.001). In the hierarchical regression, neither age nor medication dose were significant predictors, but PMBR did predict the severity of the core deficit (F (1, 23) = 12.6, P=0.002, R² = -.592). Discussion Scores for the two latent variables representing impoverishment and disorganization of mental activity in schizophrenia can be derived from each of three symptom rating scales. A composite measure of impoverishment, disorganization, impaired cognition and impaired role function reflects an underlying psychopathological process that might be described as the core deficit of classical schizophrenia.

scholarly journals Quantifying the Core Deficit in Classical Schizophrenia

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Mohanbabu Rathnaiah ◽  
Elizabeth B Liddle ◽  
Lauren Gascoyne ◽  
Jyothika Kumar ◽  
Mohammad Zia Ul Haq Katshu ◽  
...  
Keyword(s):  
Latent Variable ◽  
Factor Model ◽  
Mental Activity ◽  
Brain Disorders ◽  
Role Function ◽  
The Core ◽  
Core Deficit ◽  
Confirmatory Factor ◽  
Predicting Outcome ◽  
Impaired Cognition

Abstract In the classical descriptions of schizophrenia, Kraepelin and Bleuler recognized disorganization and impoverishment of mental activity as fundamental symptoms. Their classical descriptions also included a tendency to persisting disability. The psychopathological processes underlying persisting disability in schizophrenia remain poorly understood. The delineation of a core deficit underlying persisting disability would be of value in predicting outcome and enhancing treatment. We tested the hypothesis that mental disorganization and impoverishment are associated with persisting impairments of cognition and role function, and together reflect a latent core deficit that is discernible in cases diagnosed by modern criteria. We used Confirmatory Factor Analysis to determine whether measures of disorganization, mental impoverishment, impaired cognition, and role functioning in 40 patients with schizophrenia represent a single latent variable. Disorganization scores were computed from the variance shared between disorganization measures from 3 commonly used symptom scales. Mental impoverishment scores were computed similarly. A single factor model exhibited a good fit, supporting the hypothesis that these measures reflect a core deficit. Persisting brain disorders are associated with a reduction in post-movement beta rebound (PMBR), the characteristic increase in electrophysiological beta amplitude that follows a motor response. Patients had significantly reduced PMBR compared with healthy controls. PMBR was negatively correlated with core deficit score. While the symptoms constituting impoverished and disorganized mental activity are dissociable in schizophrenia, nonetheless, the variance that these 2 symptom domains share with impaired cognition and role function, appears to reflect a pathophysiological process that might be described as the core deficit of classical schizophrenia.

scholarly journals Quantfying the disorganization and the core deficit in classical schizophrenia

BJPsych Open ◽  
2021 ◽  
Vol 7 (S1) ◽  
pp. S283-S283
Author(s):  
Mohan Rathnaiah ◽  
Elizabeth B Liddle ◽  
Lauren Gascoyne ◽  
Jyothika Kumar ◽  
Mohammad Zia Ul-Haq Katshu ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Patient Group ◽  
Schizoaffective Disorder ◽  
Latent Variable ◽  
Rating Scales ◽  
Healthy Controls ◽  
Single Factor ◽  
Role Function ◽  
The Core ◽  
Core Deficit

AimsTo derive scores for mental disorganization and impoverishment from commonly used rating scales, and test the hypothesis that disorganization and impoverishment, along with impaired cognition and role-function reflect a latent variable that is a plausible candidate for the putative core deficit.BackgroundFor more than 100 years, disorganization and impoverishment of mental activity have been recognised as fundamental symptoms of schizophrenia. These symptoms may reflect a core brain process underlying persisting disability. Delusions and hallucinations have been regarded as accessory features. The psychopathological processes predisposing to persisting disability in schizophrenia are poorly understood. The delineation of a core deficit underlying persisting disability would be potentially of great value in predicting outcome and developing improved treatment.MethodPatients aged 18–55 years were included if: they satisfied DSM IV criteria for schizophrenia or schizoaffective disorder. Healthy controls were recruited by public advertisement and selected to match the patient group in age and sex. Study sample included 39 participants with schizophrenia, 1 with schizoaffective disorder and 44 matched healthy controls. We derived disorganization and impoverishment scores from three symptom scales: PANSS, SSPI and CASH. We computed composite scores for disorganization and for impoverishment and employed Confirmatory Factor Analysis to test the hypothesis that a single factor accounts for the relationships between disorganization, impoverishment, cognitive impairment and impaired role function. We assessed the relationship between this latent “core deficit” and diminished Post Movement Beta Rebound (PMBR), an electrophysiological measure from Magnetoencephalography (MEG), associated with persisting brain disorders.ResultFit indices for the single factor model from CFA indicated a good fit: χ2(2) = 1.817, p = .403; RMSEA <.001 GFI = .979. PMBR was significantly reduced in the schizophrenia group compared to healthy controls, t (68) = 3.55, p < .001. Within the patient group, PMBR was significantly and negatively correlated with the CFA factor scores representing the Core Deficit score, r=−.543, p < .01, indicating that high core deficit scores were associated with reduced PMBR. PMBR was significantly correlated with the composite Disorganization score, r=−.521, p < .001.ConclusionOur findings demonstrate that the shared variance between impoverishment (psychomotor poverty); disorganization; cognitive impairment; and impaired role function can be accounted for by a latent variable that can reasonably be described as the core deficit of classical schizophrenia. The demonstration that the severity of the putative core deficit is correlated with the reduction in PMBR provides evidence that the core deficit is associated with an identifiable abnormality of brain dysfunction.

Probability-Based and Measurement-Related Hypotheses With Full Restriction for Investigations by Means of Confirmatory Factor Analysis

Methodology ◽  
2011 ◽  
Vol 7 (4) ◽  
pp. 157-164
Author(s):  
Karl Schweizer
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Cognitive Processing ◽  
Latent Variables ◽  
Repeated Measures ◽  
Latent Variable ◽  
Model Fit ◽  
Repeated Measures Data ◽  
Confirmatory Factor ◽  
And Performance

Probability-based and measurement-related hypotheses for confirmatory factor analysis of repeated-measures data are investigated. Such hypotheses comprise precise assumptions concerning the relationships among the true components associated with the levels of the design or the items of the measure. Measurement-related hypotheses concentrate on the assumed processes, as, for example, transformation and memory processes, and represent treatment-dependent differences in processing. In contrast, probability-based hypotheses provide the opportunity to consider probabilities as outcome predictions that summarize the effects of various influences. The prediction of performance guided by inexact cues serves as an example. In the empirical part of this paper probability-based and measurement-related hypotheses are applied to working-memory data. Latent variables according to both hypotheses contribute to a good model fit. The best model fit is achieved for the model including latent variables that represented serial cognitive processing and performance according to inexact cues in combination with a latent variable for subsidiary processes.

Conceptualizing Protective Family Context and Its effect on Substance Use: Comparisons Across Diverse Ethnic-Racial Youth

2019 ◽  
Author(s):  
Kevin Constante ◽  
Edward Huntley ◽  
Emma Schillinger ◽  
Christine Wagner ◽  
Daniel Keating
Keyword(s):  
Substance Use ◽  
Measurement Invariance ◽  
Latent Variables ◽  
Latent Variable ◽  
Path Model ◽  
Family Context ◽  
Partial Metric ◽  
Racial Groups ◽  
Protective Methods ◽  
Family Variables

Background: Although family behaviors are known to be important for buffering youth against substance use, research in this area often evaluates a particular type of family interaction and how it shapes adolescents’ behaviors, when it is likely that youth experience the co-occurrence of multiple types of family behaviors that may be protective. Methods: The current study (N = 1716, 10th and 12th graders, 55% female) examined associations between protective family context, a latent variable comprised of five different measures of family behaviors, and past 12 months substance use: alcohol, cigarettes, marijuana, and e-cigarettes. Results: A multi-group measurement invariance assessment supported protective family context as a coherent latent construct with partial (metric) measurement invariance among Black, Latinx, and White youth. A multi-group path model indicated that protective family context was significantly associated with less substance use for all youth, but of varying magnitudes across ethnic-racial groups. Conclusion: These results emphasize the importance of evaluating psychometric properties of family-relevant latent variables on the basis of group membership in order to draw appropriate inferences on how such family variables relate to substance use among diverse samples.

scholarly journals Interpretable Variational Graph Autoencoder with Noninformative Prior

2021 ◽  
Vol 13 (2) ◽  
pp. 51
Author(s):  
Lili Sun ◽  
Xueyan Liu ◽  
Min Zhao ◽  
Bo Yang
Keyword(s):  
Latent Variables ◽  
Latent Variable ◽  
Expert Knowledge ◽  
Structural Information ◽  
Standard Normal Distribution ◽  
Noninformative Prior ◽  
Latent Space ◽  
Distribution Parameters ◽  
Standard Normal ◽  
Low Dimensional

Variational graph autoencoder, which can encode structural information and attribute information in the graph into low-dimensional representations, has become a powerful method for studying graph-structured data. However, most existing methods based on variational (graph) autoencoder assume that the prior of latent variables obeys the standard normal distribution which encourages all nodes to gather around 0. That leads to the inability to fully utilize the latent space. Therefore, it becomes a challenge on how to choose a suitable prior without incorporating additional expert knowledge. Given this, we propose a novel noninformative prior-based interpretable variational graph autoencoder (NPIVGAE). Specifically, we exploit the noninformative prior as the prior distribution of latent variables. This prior enables the posterior distribution parameters to be almost learned from the sample data. Furthermore, we regard each dimension of a latent variable as the probability that the node belongs to each block, thereby improving the interpretability of the model. The correlation within and between blocks is described by a block–block correlation matrix. We compare our model with state-of-the-art methods on three real datasets, verifying its effectiveness and superiority.

Information Matrices in Latent-Variable Models

1989 ◽  
Vol 14 (4) ◽  
pp. 335-350 ◽  
Author(s):  
Robert J. Mislevy ◽  
Kathleen M. Sheehan
Keyword(s):  
Latent Variables ◽  
Latent Variable ◽  
Information Matrix ◽  
Missing Information ◽  
Variable Model ◽  
Related Information ◽  
Expected Information ◽  
The Difference ◽  
Information Matrices ◽  
Practical Implications

The Fisher, or expected, information matrix for the parameters in a latent-variable model is bounded from above by the information that would be obtained if the values of the latent variables could also be observed. The difference between this upper bound and the information in the observed data is the “missing information.” This paper explicates the structure of the expected information matrix and related information matrices, and characterizes the degree to which missing information can be recovered by exploiting collateral variables for respondents. The results are illustrated in the context of item response theory models, and practical implications are discussed.

Comorbidity: Cognition and biology count!

2010 ◽  
Vol 33 (2-3) ◽  
pp. 168-170 ◽  
Author(s):  
Orly Rubinsten ◽  
Avishai Henik
Keyword(s):  
Behavioral Disorders ◽  
The Core ◽  
Brain Levels ◽  
Core Deficit

AbstractWe agree with Cramer et al. that pure cases of behavioral disorders with no symptom overlaps are rare. However, we argue that disorders do exist and the network idea is limited and limiting. Networks of symptoms are observed mainly at behavioral levels. The core deficit is commonly at the cognitive or brain levels, and there the story is completely different.

scholarly journals Structural Equation Modeling for the Effect of Main Factors on Abortion Issue

2019 ◽  
Vol 7 (1) ◽  
pp. 1-13
Author(s):  
Aras Jalal Mhamad ◽  
Renas Abubaker Ahmed
Keyword(s):  
Structural Equation Modeling ◽  
Latent Variables ◽  
Latent Variable ◽  
Structural Equation ◽  
Close Contact ◽  
Maternity Hospital ◽  
Equation Modeling ◽  
Research Model ◽  
Statistical Tools ◽  
Main Factors

       Based on medical exchange and medical information processing theories with statistical tools, our study proposes and tests a research model that investigates main factors behind abortion issue. Data were collected from the survey of Maternity hospital in Sulaimani, Kurdistan-Iraq. Structural Equation Modelling (SEM) is a powerful technique as it estimates the causal relationship between more than one dependent variable and many independent variables, which is ability to incorporate quantitative and qualitative data, and it shows how all latent variables are related to each other. The dependent latent variable in SEM which have one-way arrows pointing to them is called endogenous variable while others are exogenous variables. The structural equation modeling results reveal is underlying mechanism through which statistical tools, as relationship between factors; previous disease information, food and drug information, patient address, mother’s information, abortion information, which are caused abortion problem. Simply stated, the empirical data support the study hypothesis and the research model we have proposed is viable. The data of the study were obtained from a survey of Maternity hospital in Sulaimani, Kurdistan-Iraq, which is in close contact with patients for long periods, and it is number one area for pregnant women to obtain information about the abortion issue. The results shows arrangement about factors effectiveness as mentioned at section five of the study. This gives the conclusion that abortion problem must be more concern than the other pregnancy problem.

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